Author: Jonathan Wu

When data integration software first appeared in the early 1990’s, the ability to use a graphical user interface to design data flows and transformations that automatically generated SQL statements was powerful because it alleviated the burden and significantly reduced the time of manually creating custom code. By its inherent design, data integration software provides a consistent method for moving and integrating data that can be easily maintained by individuals who did not design the data flows. The implementation effort of data integration software is significant at the beginning of all information management projects. Once the data movement and integration activities have been defined, maintaining the data integration activities typically requires minimal effort since there are few or seldom changes to the data integration jobs.

Status Quo Pricing

The standard pricing model for data integration software is based upon the number of individuals that will be using it. In many cases, other factors such as the number of core, node, CPU speed or connectors complicate the pricing for many data integration software vendors. While this approach is prevalent for data integration software, does it make sense?

Diyotta’s Pricing Philosophy

The frustration arising from working with traditional data integration technologies and having to maintain custom coded scripts in big data environments was the inspiration for Diyotta’s Modern Data Integration Suite. The technology was built by data integration experts with extensive experience working with many existing data integration software packages and dealing with their complex pricing models. They began questioning the architectures and standard pricing models. We believe that pricing for data integration technology should be based upon the economic utility or value that the software provides.

Since there are typically more individuals using data integration software to create data movement and integration activities and fewer individuals needed to maintain those activities, licensing the software based upon the number of users does not make sense. Using factors such as the number of cores, nodes or CPU speed as factors of pricing does not make sense either because there is no correlation to the economic value derived from the data integration software.

Diyotta’s Pricing Model

Our approach to data integration is unique and so is our pricing model. The annual subscription for Diyotta’s MDI Suite is based upon two factors: 1. Components (Controller, Agent and Platform) and 2. Environments (Production and Non-production). Using the MDI Suite in a development or non-production environment is less expensive than using it in a production environment due to the correlation of economic value provided.

Starting at $5,000 per month, unlimited number of individuals within your organization can experience the orchestration and automation capabilities of Diyotta’s MDI Suite for moving and integrating big data. For organizations with revenue/funding of less than $50 million, reduced annual subscriptions are available.